You're currently viewing an old version of this dataset. To see the current version, click here.

Lifelong Hyper-Policy Optimization with Multiple Importance Sampling

The authors propose a lifelong RL approach that learns a hyper-policy, whose input is time, that outputs the parameters of the policy to be queried at that time.

Data and Resources

Cite this as

Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello Restelli (2024). Dataset: Lifelong Hyper-Policy Optimization with Multiple Importance Sampling. https://doi.org/10.57702/ron28kil

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2112.06625
Author Pierre Liotet
More Authors
Francesco Vidaich
Alberto Maria Metelli
Marcello Restelli